System and method for detecting target materials using a vis-nir detector

ABSTRACT

The present disclosure provides systems and methods for determining the presence of a target material in a sample. In general terms, the system and method disclosed herein provide collecting interacted photons from a sample having a target material. The interacted photons are passed through a tunable filter to a VIS-NIR detector where the VIS-NIR detector generates a VIS-NIR hyperspectral image representative of the filtered interacted photons. The hyperspectral image of the filtered interacted photons is analyzed by comparing the hyperspectral image of the filtered interacted phtons to known hyperspectral images to identify the presence of a target material in a sample. The systems and methods disclosed herein provide easy identification of the presence of a target material in a sample.

CROSS-REFERENCE TO RELATED APPLICATION

This applications claims benefit of and priority to U.S. ProvisionalApplication Ser. No. 61/796,962 entitled “Portable VIS-NIR Detector andMethod for use thereof” and filed Mar. 15, 2013, the disclosure of whichis incorporated by reference herein in its entirety.

BACKGROUND

Spectroscopic imaging combines digital imaging and molecularspectroscopy techniques, which can include Raman scattering,fluorescence, photoluminescence, ultraviolet, visible and infraredabsorption spectroscopies. When applied to the chemical analysis ofmaterials, spectroscopic imaging is commonly referred to as chemicalimaging. Instruments for performing spectroscopic (i.e. chemical)imaging typically comprise an illumination source, image gatheringoptics, focal plane array imaging detectors and imaging spectrometers.

In general, the sample size determines the choice of an image gatheringoptic. For example, a microscope is typically employed for the analysisof sub-micron to millimeter spatial dimension samples. For largerobjects, in the range of millimeter to meter dimensions, macro lensoptics are appropriate. For samples located within relativelyinaccessible environments, flexible fiberscope or rigid borescopes canbe employed. For very large scale objects, such as planetary objects,telescopes are appropriate image gathering optics.

For detection of images formed by the various optical systems,two-dimensional, imaging focal plane array (“FPA”) detectors aretypically employed. The choice of FPA detector is governed by thespectroscopic technique employed to characterize the sample of interest.For example, silicon (Si) charge-coupled device (“CCD”) detectors orCMOS detectors are typically employed with visible wavelengthfluorescence and Raman spectroscopic imaging systems, while indiumgallium arsenide (“InGaAs”) FPA detectors are typically employed withnear-infrared spectroscopic imaging systems.

Spectroscopic imaging of a sample is commonly implemented by one of twomethods. First, point-source illumination can be used on a sample tomeasure the spectra at each point of the illuminated area. Second,spectra can be collected over the entire area encompassing a samplesimultaneously using an electronically tunable optical imaging filtersuch as an acousto-optic tunable filter (AOTF), a multi-conjugatetunable filter (MCF), or a liquid crystal tunable filter (LCTF). Here,the organic material in such optical filters is actively aligned byapplied voltages to produce the desired bandpass and transmissionfunction. The spectra obtained for each pixel of an image forms acomplex data set referred to as a hyperspectral image. Hyperspectralimages may contain the intensity values at numerous wavelengths or thewavelength dependence of each pixel element in the image. Multivariateroutines, such as chemometric techniques, may be used to convert spectrato classifications.

Spectroscopic devices operate over a range of wavelengths due to theoperation ranges of the detectors or tunable filters possible. Thisenables analysis in the Ultraviolet (UV), visible (VIS), near infrared(NIR), short-wave infrared (SWIR), mid infrared (MIR) wavelengths, longwave infrared wavelengths (LWIR), and to some overlapping ranges.

The Applicants hereto have found that use of hyperspectral imaging inthe VIS-NIR range of wavelengths provides a useful tool for theidentification of target materials in a sample.

SUMMARY

In an embodiment a system for identifying a target material in a samplemay include a first collection optic configured to collect a pluralityof interacted photons. Interacted photons are those photons that haveinteracted with the sample. The system further includes a tunable filterconfigured to filter a first plurality of interacted photons collectedfrom the first collection optic. The tunable filter is configured tofilter the first plurality of interacted photons into a plurality ofwavelengths to generate filtered interacted photons. In the system, aVIS-NIR detector is configured to detect the filtered interacted photonsand to generate a VIS-NIR hyperspectral image representation of thefiltered interacted photons. The system further includes a processorconfigured to analyze the VIS-NIR hyperspectral image of the filteredinteracted phtons by comparing the VIS-NIR hyperspectral image of thefiltered interacted photons to a database of known VIS-NIR hyperspectralimages in order to identify the presence of the target material.

In another embodiment, the system may include a second collection opticconfigured to collect a second plurality of interacted photons. In oneembodiment a RGB detector is configured to detect the second pluralityof interacted photons and to generate a RGB image representation of thesecond plurality of interacted photons.

In another embodiment the system may include an illumination sourceconfigured to provide photons that interact with a sample to generateinteracted photons. In one embodiment, the system described herein maybe housed in a portable or handheld device.

In an embodiment disclosed herein, a method for identifying targetmaterial in a sample is provided. The method includes collecting aplurality of interacted photons from the plurality of interacted photonshave interacted with the sample. The method further provides directingthe first plurality of interacted photons through a tunable filter togenerate a plurality of filtered photons where the filter separates thephotons into a plurality of wavelengths. The method further providesdetecting the first plurality of interacted photons with a VIS-NIRhyperspectral detector where the VIS-NIR detector generates ahyperspectral representation of the first plurality of filtered photons.The method further includes analyzing the VIS-NIR hyperspectral image ofthe filtered interacted photons by comparing the VIS-NIR hyperspectralimage of the filtered interacted photons to a database of knownhyperspectral images to identify the presence of the target material.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a schematic illustration of an illustrative system foridentifying a target material according to an embodiment;

FIG. 1B is a schematic illustration of an illustrative portable systemfor identifying a target material according to an embodiment;

FIG. 1C is a schematic illustration of an illustrative handheld systemfor identifying a target material according to an embodiment;

FIG. 2 is a flow-chart illustrating an illustrative method foridentifying a target material according to an embodiment;

FIG. 3 illustrates a sample material having two ink compositions whereone ink is a target material according to an embodiment;

FIG. 4 illustrates a VIS-NIR hyperspectral image of a sample identifyinga target ink in the sample according to an embodiment; and

FIG. 5 illustrates a VIS-NIR hyperspectral image of a kidney sampleidentifying blood vessels and fat tissue in the kidney sample accordingto an embodiment.

DETAILED DESCRIPTION

Reference will now be made in detail to embodiments of the presentdisclosure, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the specification to refer to the same or like parts.

FIGS. 1A, 1B, and 1C illustrate exemplary embodiments of a system 100according to embodiments herein. In one embodiment of the presentsystem, the system 100 is housed in a portable or handheld unit. FIG. 1Band FIG. 1C illustrate an example of a portable and a handheld unit,respectively, featuring the system 100. In another embodiment, thesystem 100 contemplates designs to accommodate other portableconfigurations, such as, for example, a design having objectives onmovable arms and the like.

Referring now to FIG. 1A, the system 100 comprises a RGB opticalsubsystem 105. The RGB optical subsystem 105 includes a RGB collectionoptic 110 b and a RGB detector 120 b. In one embodiment, the RGBcollection optic 110 b is a RGB lens. The RGB collection optic 110 b isconfigured to collect a plurality of photons that have interacted with asample. As used herein, “interacted photons” comprise photons scatteredby a sample, photons absorbed by a sample, photons reflected by asample, photons emitted by a sample or any combination thereof. In oneembodiment, the RGB detector 120 b is a RGB camera. The RGB collectiondetector 120 b is configured to detect the interacted photons that havebeen collected from the RGB collection optic 110 b. In one embodiment,the RGB optical subsystem 105 generates a RGB image representative of alocation on a sample representative of the interacted photons collectedfrom the RGB collection optic 110 b.

In another embodiment, the system 100 comprises a VIS-NIR subsystem 106.The VIS-NIR subsystem 106 may include a VIS-NIR collection optic 110 a,a VIS-NIR tunable filter 115 and a VIS-NIR detector 120 a. The VIS-NIRdetector, as used herein, may be configured to detect any wavelength asapparent to those of skill in the art in view of this disclosure. In oneembodiment, the VIS-NIR detector is configured to detect wavelengthsfrom about 400 nm to about 1,100 nm. It is understood that the VIS-NIRdetector can be configured to detect wavelengths in any subset ofwavelengths within those disclosed herein based on a subset ofwavelengths that may be of particular interest. In one embodiment, theVIS-NIR collection optic 110 a is a VIS-NIR lens. The VIS-NIR collectionoptic 110 a is configured to collect a plurality of photons that haveinteracted with the sample. The VIS-NIR tunable filter 115 is configuredin a sequential manner with the VIS-NIR collection optic 110 a to filterphotons collected from the VIS-NIR collection optic. In anotherembodiment, the VIS-NIR detector 120 a is sequentially configured withthe VIS-NIR tunable filter to detect photons filtered by the VIS-NIRtunable filter 115. The VIS-NIR detector 120 a, upon detection of thefiltered photons, generates a VIS-NIR hyperspectral image representativeof the filtered photons. In one embodiment, the VIS-NIR hyperspectralimage contemplated herein is a collection of data images over a rangeof, for example, from 400 nm to about 1,100 nm. The VIS-NIRhyperspectral imaging provides detailed color information to a user andprovides good color discrimination between different materials ofinterest.

In one embodiment, the system 100 generates the RGB image and theVIS-NIR hyperspectral image simultaneously. That is, the system 100 canoperate to generate a RGB image while at the same time the system 100can generate a VIS-NIR hyperspectral image without the need forconsecutively detecting the RGB image and the VIS-NIR hyperspectralimage.

The system 100 can be used to determine the presence of the targetmaterial in the sample. Applications where the system 100 would besuitable for providing identification of a target include, for example,applications in the areas of anatomic pathology (includingdermatological applications), forensic crime scene investigation orreconstruction (blood/body fluid detection and analysis), counterfeitdetection (including art work and questioned/security documents), threatdetection (chemical, biological, and explosive materials, otherhazardous materials, and drugs), and pharmaceuticals includingingredient-specific particle sizing and other applications as would beapparent to those of skill in the art in view of this disclosure.Identification of the presence of a target material in the sample mayinclude detecting, identifying, classifying, or any combination thereof.

In one embodiment of the system, the VIS-NIR tunable filter 115 isconfigured to filter a plurality of interacted photons into a pluralityof wavelength bands. In another embodiment, the VIS-NIR tunable filter115 may comprise a liquid crystal tunable filter, a multi-conjugatetunable filter, an acousto-optical tunable filters, a Lyot liquidcrystal tunable filter, a Evans Split-Element liquid crystal tunablefilter, a Solc liquid crystal tunable filter, a Ferroelectric liquidcrystal tunable filter, a Fabry Perot liquid crystal tunable filter, orany combination thereof.

In one embodiment of the present system 100, the VIS-NIR detector 120 afeatures a focal plane array. In another embodiment of the presentsystem, the VIS-NIR detector 120 a may comprise a detector including,for example, a InGaAs detector, a CMOS detector, an InSb detector, a MCTdetector, an ICCD detector, a CCD detector, or any combination thereof.

The system 100 further comprises an field programmable gate array(“FPGA”) 125 or interface logic that is in communication with theVIS-NIR detector 120 a. In another embodiment, the FPGA 125 is incommunication with the RGB detector 120 b. The FPGA 125 may furtherinclude a FPGA memory source 130. The FPGA 125 may further be incommunication with an application processor 135. In one embodiment, theapplication processor 135 is, for example, a CPU, a digital signalprocessor, or combinations thereof. The application processor 135 mayfurther be in communication with interface features or peripherals, suchas, for example, a user input 150, such as input buttons, an externalinterface 145, such as a USB, a user display 150, such as a LCD paneldisplay, storage memory 155, such as an SD card, application memory 160,and other peripherals as would be apparent to those of skill in the artin view of this disclosure. In one embodiment of the system 100, theFPGA 125, application processor 135, memory source 130, storage memory155, and application memory 160 are configured to operate the system 100to analyze and store collected data and store reference data. In oneembodiment, the system 100 comprises a reference database having aplurality of reference data sets where each reference data set isassociated with a known material. Each reference data set may comprise ahyperspectral image of a known material such that the hyperspectralimage obtained from the sample via the system 100 can be compared toeach reference data set to identify the sample and the target materialto determine the presence of the target material in the sample. It isunderstood that the target material is of known composition and thesystem 100 provides the capability of determining the presence of thetarget material in the sample by comparing hyperspectral images obtainedfrom the sample and the target material to known hyperspectral images toidentify the presence of the target material. The system 100distinguishes the hyperspectral image of the sample from thehyperspectral image of the target material, if present. Once theidentification of the sample and the target material are obtained by thesystem 100, the result of the identification can be reported to a userthrough the display 150. The system 100 may also comprise a battery pack145 for supplying power to the system 100.

The system 100 can be configured to operate at various distances fromthe VIS-NIR collection optic 110 a and the RGB collection optic 110 b tothe sample. The operating distance is dependent on the specifications ofthe VIS-NIR collection optic 110 a and the RGB collection optic 110 band can be about 0.5 m or greater. In one embodiment, the operatingrange of the system 100 is about 0.5 m or greater. In anotherembodiment, the operating range of the system 100 is about 5 m orgreater. In yet another embodiment, the operating range of the system100 is from about 1 m to about 20 m. In another embodiment, theoperating range of the system 100 is from about 0.5 m to about 10 m. Itis apparent to one of skill in the art that the operating range of thesystem can be configured to operate in any range within those recited.Further, in one embodiment, the system 100 is capable of operating withadjustable optics such that the operating range of the system 100 can beadjusted without the need to modify the VIS-NIR collection optic 110 aand the RGB collection optic 110 b. In another embodiment, thecollection optics may be configured to change the Field of View (“FOV”)with regard to the sample. Configuring the FOV can be accomplished by,in a fixed collection optics system, by changing the collection opticsto achieve the desired FOV or, in an adjustable collection optic system,by adjusting the collection optics to achieved the desired FOV. Thedesired FOV would be apparent to those of skill in the art in view ofthis disclosure. The system 100 can further include other opticaldevices such as, for example, additional lens, other image gatheringoptics, arrays, mirrors, beam splitters and the like. Additionalelements suitable for use with the system 100 are apparent to those ofskill in the art in view of this disclosure.

The system 100 can further be configured to generate hyperspectralimages of a sample having a target material in near real time. In oneembodiment, the system 100 tracks a sample generating up to 2frames/second to allow for near real time analysis of a sample.

In one embodiment, the system 100 includes an illumination source. Theillumination source can be one illumination source or a plurality ofillumination sources. The illumination source can be ambient light orlight provided to the sample from an active source working inconjunction with the system 100. In one embodiment, the illuminationsource illuminates the sample from a variety of different angles. Anactive illumination source when used with the system 100 enables thesystem to operate in low or variable light conditions. Any illuminationsources suitable for use with the system 100 can be used and suchillumination sources would be apparent to those of skill in the art inview of this disclosure.

FIG. 1B illustrates an illustrative portable system 101 for identifyinga target material in a sample according to an embodiment. The portablesystem 101 features a VIS-NIR lens 110 a and a RGB lens 110 b in closeproximity to allow for the collection of photons from a sample foranalyzing a RGB image and a VIS-NIR hyperspectral image in one step. TheVIS-NIR lens 110 a collects photons from a sample and directs thephotons through a VIS-NIR liquid crystal tunable filter (“LCTF”) 115.The photons from the VIS-NIR LCTF 115 then pass through a focusing lens118 which focus the photons before passing the photons on to the VIS-NIRcamera 120 a. The VIS-NIR camera 120 a detects the photons passing fromthe focusing lens 118 and generates a VIS-NIR hyperspectral imagerepresentative of the photons. A processor 135 in communication with theVIS-NIR camera 120 a analyzes the hyperspectral image to determine thepresence of the target material in a sample. The portable system 101further includes a RGB lens 110 b and a RGB camera 120 b where the RGBcamera is configured to detect photons collected from the RGB lens 110b. The RGB camera 120 b generates a RGB image representative of thephotons collected from the RGB lens 110 b. The RGB camera 120 b isfurther in communication with the processor 135 for analyzing the RGBimage. The portable system includes user interface controls 140 topermit the user to interact with the portable system 101. Further, theportable system 101 includes a display 150 for displaying informationobtained by the portable system to a user. The portable system 101further includes a power source 165 for operating the portable systemremotely.

FIG. 1C depicts an illustrative handheld system 102 to permit a user tocarry the system for identifying a target material according to anembodiment. The handheld system 102 includes a handle 117 for beingcarried by a user. The handheld system 102 further includes activeillumination sources 180 for illuminating a sample to generate photonsthat interact with a sample. The active illumination sources 180 enablethe handheld system 102 to operate in remote locations having inadequateillumination. The handheld system 102 includes a VIS-NIR collection lensaperture 106 and a RGB collection lens aperture 105 for collectingphotons generated by a sample. The handheld system 102 further includesa display 150 for conveying data obtained by the handheld system 102 toa user. In operation, the handheld system 102 operates in similarfashion to the system 100, as described herein.

FIG. 2 depicts a flow diagram of an illustrative method 200 foranalyzing a sample comprising a target material according to anembodiment. The method 200 may comprise collecting 210 a plurality ofinteracted photons from the sample comprising a target material in step210. These interacted photons may be generated by illuminating thesample using an active illumination, a passive illumination, or anycombination thereof. The interacted photons may comprise photonsscattered by the sample, photons reflected by the sample, photonsabsorbed by the sample, photons emitted by the sample, or anycombination thereof.

In one embodiment of the method 200, the interacted photons may bepassed through a tunable filter. The tunable filter is configured tofilter the interacted photons into a plurality of wavelength bands. AVIS-NIR hyperspectral image may be generated 220 representative of thesample comprising a target material. The VIS-NIR hyperspectral image maybe analyzed 230. In one embodiment, the VIS-NIR hyperspectral image isanalyzed 230 by comparing the hyperspectral image of the sample and thehyperspectral image of the target material to a reference data set wherethe reference data set includes known hyperspectral images to identifythe presence of the target material in the sample. In one embodiment,the comparison is accomplished by applying one or more chemometrictechniques. Chemometric techniques suitable for use in the methodinclude: principle components analysis, partial least squaresdiscriminate analysis, cosine correlation analysis, Euclidian distanceanalysis, k-means clustering, multivariate curve resolution, band t.entropy method, mahalanobis distance, adaptive subspace detector,spectral mixture resolution, and Bayesian fusion. It is alsocontemplated that more than one chemometric technique may be applied. Itis further contemplated that any chemometric method as known to those ofskill in the art may be applied. In one embodiment, the analysis maydetect a target material, associate the target material with a knownmaterial, detect a difference between the target and the sample, detectmore than one target in the sample, or any combination thereof.

EXAMPLES Example 1

FIG. 3 and FIG. 4 illustrate an example using the disclosed system foridentifying a target material in a sample. In this example, the VIS-NIRdetector was configured to identify the presence of one ink having adifferent composition from a second ink. In FIG. 3, a sample isillustrated where the sample includes a first black ink 305, representedby the drawn number “12,” and the second black ink 310, represented bythe drawn number “39.” Both inks were drawn on paper. Separate VIS-NIRhyperspectral spectra were obtained for each of the two different setsof black ink 305, 310. A subset of wavelengths was selected in order toidentify the presence of the first black ink 305 in the sample. FIG. 4shows the VIS-NIR detection image of the sample containing both thefirst black ink 305 and the second black ink 310. Once the VIS-NIRspectra was obtained for the sample, the VIS-NIR image was compared theknown VIS-NIR spectra for the different inks After the comparison, thepresence of the first black ink 305 was identified in the field of view.The first black ink 305 is shown with a green hue and is highlighted inthe green boxes. In this Example, a VIS-NIR detector was used to producenear real-time detections of the presence of the first black ink 305 inthe field of view.

Example 2

FIG. 5 illustrates another example using the disclosed system foridentifying a target material in a sample. In this example, a VIS-NIRdetector is configured to identify blood vessels and fat tissue fromother tissue parts of a kidney. Separate VIS-NIR spectra was obtainedfor kidney sample tissues as well as for blood vessels and fat tissue. Asubset of wavelengths was selected to identify the presence of bloodvessels and fat tissue. The kidney sample was analyzed by a VIS-NIRdetector producing the result shown in FIG. 5. The VIS-NIR spectra ofthe kidney sample was compared to known VIS-NIR spectra of a kidneysample, blood vessels, and fat tissue. After the comparison, bloodvessels and fat tissue 400 were observed in the sample. The bloodvessels and fat tissue 400 show up in the VIS-NIR image having a greenhue. In this Example, a VIS-NIR detector was used to produce nearreal-time detections of the blood vessels and fat tissue within thefield of view.

While the disclosure has been described in detail in reference tospecific embodiments thereof, it will be apparent to one skilled in theart that various changes and modifications can be made therein withoutdeparting from the spirit and scope of the embodiments. Thus, it isintended that the present disclosure cover the modifications andvariations of this disclosure provided they come within the scope of theappended claims and their equivalents.

What is claimed is:
 1. A system for identifying a target material in asample, the system comprising: a first collection optic configured tocollect a plurality of interacted photons that have interacted with thesample; a tunable filter configured to filter a first plurality ofinteracted photons collected from the first collection optic into aplurality of wavelengths to generate filtered interacted photons; aVIS-NIR detector configured to detect the filtered interacted photons,wherein the VIS-NIR detector generates a VIS-NIR hyperspectral imagerepresentation of the filtered interacted photons; and a processorconfigured to analyze the VIS-NIR hyperspectral image of the filteredinteracted photons by comparing the VIS-NIR hyperspectral image of thefiltered interacted photons to a database of known VIS-NIR hyperspectralimages in order to identify the presence of the target material.
 2. Thesystem of claim 1, further comprising: a second collection opticconfigured to collect a second plurality of interacted photons; and aRGB detector configured to detect the second plurality of interactedphotons collected from the second collection optic, wherein the RGBdetector is configured to generate a RGB image representation of thesecond plurality of interacted photons.
 3. The system of claim 2,wherein the VIS-NIR hyperspectral image and the RGB image are generatedsubstantially simultaneously.
 4. The system of claim 1, furthercomprising an illumination source, wherein the illumination source isconfigured to provide photons that interact with the sample to generatethe plurality of interacted photons.
 5. The system of claim 1, whereinthe tunable filter comprises a liquid crystal tunable filter, amulti-conjugate tunable filter, an acousto-optical tunable filter, aLyot liquid crystal tunable filter, an Evans Split-Element liquidcrystal tunable filter, a Solc liquid crystal tunable filter, aFerroelectric liquid crystal tunable filter, a Fabry Perot liquidcrystal tunable filter, or any combination thereof.
 6. The system ofclaim 1, wherein the VIS-NIR detector comprises an InGaAs detector, aCMOS detector, an InSb detector, a MCT detector, an ICCD detector, a CCDdetector, or any combination thereof.
 7. The system of claim 1, whereinthe VIS-NIR detector comprises a focal plane array.
 8. The system ofclaim 1, further comprising a display configured to display analysisinformation obtained by the system to a user.
 9. The system of claim 1,further comprising a user interface configured to receive one or moreinputs from a user to interact with the system.
 10. The system of claim1, wherein the processor is further configured to analyze the VIS-NIRhyperspectral image generated from the filtered interacted photons byapplying a chemometric technique.
 11. The system of claim 10, whereinthe chemometric technique comprises principle components analysis,partial least squares discriminate analysis, cosine correlationanalysis, Euclidian distance analysis, k-means clustering, multivariatecurve resolution, band t. entropy method, mahalanobis distance, adaptivesubspace detector, spectral mixture resolution, Bayesian fusion or anycombination thereof.
 12. The system of claim 1, wherein the system ishoused in a portable or handheld unit.
 13. A method for identifying atarget material in a sample, the method comprising: collecting aplurality of interacted photons from the sample, wherein the pluralityof interacted photons have interacted with the sample; directing a firstplurality of interacted photons through a filter to generate a firstplurality of filtered photons, wherein the filter separates the firstplurality of interacted photons into a plurality of wavelengths;detecting the first plurality of filtered photons with a VIS-NIRhyperspectral image detector, generating a VIS-NIR hyperspectral imageof the first plurality of filtered photons; and analyzing the VIS-NIRhyperspectral image of the filtered interacted photons by comparing theVIS-NIR hyperspectral image of the filtered interacted photons to adatabase of known hyperspectral images to identify the presence of thetarget material.
 14. The method of claim 13, further comprising:collecting a second plurality of interacted photons; detecting thesecond plurality of interacted photons with a RGB detector, andgenerating a RGB image representation of the second plurality ofinteracted photons.
 15. The method of claim 14, wherein the VIS-NIRhyperspectral image of the filtered interacted photons and the RGB imageare generated simultaneously.
 16. The method of claim 14, furthercomprising illuminating the sample with an illumination source, whereinthe illumination source provides photons that interact with the sampleto generate the second plurality of interacted photons.
 17. The methodof claim 13, further comprising illuminating the sample with anillumination source wherein, the illumination source provides photonsthat interact with the sample to generate the first plurality ofinteracted photons.
 18. The method of claim 13, wherein analyzing theVIS-NIR hyperspectral image further comprises applying a chemometrictechnique.
 19. A system for identifying an target material in a sample,the system comprising: an illumination source configured to providephotons that interact with the sample to generate a plurality ofinteracted photons; a first collection optic configured to collect afirst plurality of interacted photons where the first plurality ofinteracted photons includes photons that have interacted with thesample; a second collection optic configured to collect a secondplurality of interacted photons where the second plurality of interactedphotons includes photons that have interacted with the sample; a tunablefilter configured to filter the first plurality of interacted photonscollected from the first collection optic into a plurality ofwavelengths to generate filtered interacted photons; a VIS-NIR detectorconfigured to detect the filtered interacted photons, wherein theVIS-NIR detector generates a VIS-NIR hyperspectral image of the filteredinteracted photons; a RGB detector configured to detect the secondplurality of interacted photons, wherein the RGB detector generates aRGB image representation of the second plurality of interacted photons;and a processor configured to analyze the VIS-NIR hyperspectral of thefiltered interacted photons and compare the VIS-NIR hyperspectral imageof the filtered interacted phtons to a database of known VIS-NIRhyperspectral images in order to identify the target material.
 20. Thesystem of claim 19 wherein the VIS-NIR hyperspectral image and the RGBimage are generated simultaneously.
 21. The system of claim 19, whereinthe tunable filter comprises a liquid crystal tunable filter, amulti-conjugate tunable filter, an acousto-optical tunable filter, aLyot liquid crystal tunable filter, an Evans Split-Element liquidcrystal tunable filter, a Solc liquid crystal tunable filter, aFerroelectric liquid crystal tunable filter, a Fabry Perot liquidcrystal tunable filter, or any combination thereof.
 22. The system ofclaim 19, wherein the VIS-NIR detector comprises a InGaAs detector, aCMOS detector, an InSb detector, a MCT detector, an ICCD detector, a CCDdetector, or any combination thereof.
 23. The system of claim 19,wherein the VIS-NIR detector comprises a focal plane array.
 24. Thesystem of claim 19, further comprising a display configured to displayVIS-NIR hyperspectral analysis information, RGB image information, orany combination thereof obtained by the system to a user.
 25. The systemof claim 19, further comprising a user interface configured to receiveone or more inputs from a user to interact with the system.
 26. Thesystem of claim 19, wherein the processor is further configured toanalyze the VIS-NIR hyperspectral image of the filtered interactedphotons by applying a chemometric technique.
 27. The system of claim 26,wherein the chemometric technique comprises: principle componentsanalysis, partial least squares discriminate analysis, cosinecorrelation analysis, Euclidian distance analysis, k-means clustering,multivariate curve resolution, band t. entropy method, mahalanobisdistance, adaptive subspace detector, spectral mixture resolution,Bayesian fusion or any combination thereof.
 28. The system of claim 19,wherein the system is housed in a portable or handheld unit.